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Adaptive NN-based finite-time trajectory tracking control of wheeled robotic systems

  • Special Issue on Computational Intelligence-based Control and Estimation in Mechatronic Systems
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Abstract

The trajectory tracking and finite-time control problems of wheeled robotic systems with nonlinear dynamics and uncertainties are investigated in this paper. An adaptive neural network (NN)-based control technique is developed to deal with the nonlinearities and uncertainties. Then, finite-time dynamic control and kinematic control schemes are constructed on the basis of the adaptive estimations to remedy the negative influence of uncertainties and nonlinearities. Specific forward and azimuthal angular velocities are developed by using NN-based kinematic control schemes to obtain the finite-time tracking of the desired position trajectory for the wheeled robotic system. Furthermore, the asymptotic tracking of the specific forward and azimuthal angular velocities is further achieved based on the finite-time dynamic control schemes with uncertainties and nonlinear dynamics. The efficacy of the developed finite-time tracking control approach is substantiated by a robotic system.

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References

  1. Krzysztof K, Dariusz P (2004) Modeling and control of a 4-wheel skid steering mobile robot. Int J Appl Math Comput Sci 14(4):477–496

    MathSciNet  MATH  Google Scholar 

  2. Kanayama Y, Kimura Y, Miyazaki F, Noguchi T (1991) A stable tracking control method for a non-holonomic mobile robot. In: Proceedings of the IEEE/RSJ international workshop on intellligent robots and systems, Osaka, Japan, p 1236–1241

  3. Khoshnam S, Mohammad SA, Ahmadreza T (2011) Adaptive trajectory tracking control of a differential drive wheeled mobile robot. Robotica 29(3):391–402

    Google Scholar 

  4. Zhang J, Wang H, Zheng J, Cao Z, Man Z, Yu M, Chen L (2020) Adaptive sliding mode-based lateral stability control of steer-by-wire vehicles with experimental validations. IEEE Trans Veh Technol. https://doi.org/10.1109/TVT.2020.3003326

    Article  Google Scholar 

  5. Jin X, Che W-W, Wu Z-G, Zhao Z (2021) Adaptive consensus and circuital implementation of a class of faulty multi-agent systems. IEEE Trans Syst Man Cybern. https://doi.org/10.1109/TSMC.2020.2995802

    Article  Google Scholar 

  6. Deng C, Yang G-H (2019) Distributed adaptive fault-tolerant control approach to cooperative output regulation for linear multi-agent systems. Automatica 103:62–68

    MathSciNet  MATH  Google Scholar 

  7. Jin X, Che W-W, Wu Z-G, Wang H (2021) Analog control circuit designs for a class of continuous-time adaptive fault-tolerant control systems. IEEE Trans Cyber. https://doi.org/10.1109/TCYB.2020.3024913

    Article  Google Scholar 

  8. Jin X, Lü S, Yu J (2021) Adaptive NN-based consensus for a class of nonlinear multiagent systems with actuator faults and faulty networks. IEEE Trans Neural Netw Learn Syst. https://doi.org/10.1109/TNNLS.2021.3053112

    Article  Google Scholar 

  9. Han C, Liu Z, Yi J (2018) Immersion and invariance adaptive control with \(\sigma\)-modification for uncertain nonlinear systems. J Frankl Inst 355(5):2091–2111

    MathSciNet  MATH  Google Scholar 

  10. Jin X, Wang S, Qin J, Zheng WX, Kang Y (2018) Adaptive fault-tolerant consensus for a class of uncertain nonlinear second-order multi-agent systems with circuit implementation. IEEE Trans Circuits Syst I Reg Papers 65(7):2243–2255

    MathSciNet  MATH  Google Scholar 

  11. Wang H, Mi CL, Cao ZW, Zheng JC, Man ZH, Jin XZ, Tang H (2020) Precise discrete-time steering control for robotic fish based on data-assisted technique and super-twisting-like algorithm. IEEE Trans Ind Electron 67(12):10587–10599

    Google Scholar 

  12. Deng C, Wen CY (2020) Distributed resilient observer-based fault-tolerant control for heterogeneous multiagent systems under actuator faults and DoS attacks. IEEE Trans Control Netw Syst 7:1308–1318

    MathSciNet  MATH  Google Scholar 

  13. Qin J, Ma Q, Yu X, Wang L (2020) On synchronization of dynamical systems over directed switching topology: An algebraic and geometric perspective. IEEE Trans Autom Control 65(12):5083–5098

    MATH  Google Scholar 

  14. Jin X, Lü S, Qin J, Zheng WX (2020) Auxiliary constrained control of a class of fault-tolerant systems. IEEE Trans Syst Man Cybern Syst. https://doi.org/10.1109/TSMC.2019.2911269

    Article  Google Scholar 

  15. Sun ZQ, Xia YQ, Liu K (2017) Disturbance rejection MPC for tracking of wheeled mobile robot. IEEE Trans Mech 22(6):2576–2587

    Google Scholar 

  16. Qin J, Fu W, Zheng WX, Gao H (2017) On the bipartite consensus for generic linear multiagent systems with input saturation. IEEE Trans Cyber 47(8):1948–1958

    Google Scholar 

  17. Hu Y, Wang H, Cao Z, Zheng J, Ping Z, Chen L, Jin X (2020) Extreme-learning-machine-based FNTSM control strategy for electronic throttle. Neural Comput Appl 32:14507–14518

    Google Scholar 

  18. Zhang J, Wang H, Cao Z, Zheng J, Yu M, Yazdani A, Shahnia F (2020) Fast nonsingular terminal sliding mode control for permanent magnet linear motor via ELM. Neural Comput Appl 32:14447–14457

    Google Scholar 

  19. Qin J, Gao H, Zheng WX (2015) Exponential synchronization of complex networks of linear systems and nonlinear oscillators: a unified analysis. IEEE Trans Neural Netw Learn Syst 26(3):510–521

    MathSciNet  Google Scholar 

  20. Jin X, Zhao X, Yu J, Wu X, Chi J (2020) Adaptive fault-tolerant consensus for a class of leader-following systems using neural network learning strategy. Neural Networks 121:474–483

    MATH  Google Scholar 

  21. Hu Y, Wang H (2020) Robust tracking control for vehicle electronic throttle using adaptive dynamic sliding mode and extended state observer. Mech Syst Signal Process 135:1063751–10637518

    Google Scholar 

  22. Lü SY, Jin XZ, Wang H, Deng C (2021) Robust adaptive estimation and tracking control for perturbed cyber-physical systems against denial of service. Appl Math Comput. https://doi.org/10.1016/j.amc.2021.126255

    Article  MathSciNet  MATH  Google Scholar 

  23. Jin X, Lü S, Deng C, Chadli M (2021) Distributed adaptive security consensus control for a class of multi-agent systems under network decay and intermittent attacks. Inf Sci 547:88–102

    MathSciNet  MATH  Google Scholar 

  24. Wang H, Li ZH, Jin XZ, Huang YZ, Kong HF, Yu M, Ping ZW, Sun Z (2018) Adaptive integral terminal sliding mode control for automobile electronic throttle via an uncertainty observer and experimental validation. IEEE Trans Veh Technol 67(9):8129–8143

    Google Scholar 

  25. Chen L, Wang H, Huang Y, Ping Z, Yu M, Ye M, Hu Y (2020) Robust hierarchical terminal sliding mode control of two-wheeled self-balancing vehicle using perturbation estimation. Mech Syst Signal Process 139:106584–106584

    Google Scholar 

  26. Ye M, Wang H (2020) Robust adaptive integral terminal sliding mode control for steer-by-wire systems based on extreme learning machine. Comput Electr Eng 86:106756

    Google Scholar 

  27. Wang H, He P, Yu M, Liu L, Kong H, Man Z (2016) Adaptive neural network sliding mode control for steer-by-wire vehicle stability control. J Intell Fuzzy Syst 31(2):885–902

    MATH  Google Scholar 

  28. Yang JM, Kim JH (1999) Sliding mode control for trajectory tracking of nonholonomic wheeled mobile robots. IEEE Trans Robot Autom 15(3):578–587

    Google Scholar 

  29. Li L, Wang T, Xia Y, Zhou Ning (2020) Trajectory tracking control for wheeled mobile robots based on nonlinear disturbance observer with extended Kalman filter. J Frankl Inst 357(13):8491–8507

    MathSciNet  MATH  Google Scholar 

  30. Jin X, Yu J, Qin J, Zheng WX, Chi J (2021) Adaptive perturbation rejection control and driving voltage circuit designs of wheeled mobile robots. J Frankl Inst 358(2):1185–1213

    MathSciNet  MATH  Google Scholar 

  31. Kamel MA, Zhang Y, Yu X (2015) Fault-tolerant cooperative control of multiple wheeled mobile robots under actuator faults. IFAC-PapersOnLine 48(21):1152–1157

    Google Scholar 

  32. Martinez EA, Rios H, Mera M (2021) Robust tracking control design for unicycle mobile robots with input saturation. Control Eng Pract 107:104676

    Google Scholar 

  33. Jin X (2018) Fault-tolerant iterative learning control for mobile robots non-repetitive trajectory tracking with output constraints. Automatica 94:63–71

    MathSciNet  MATH  Google Scholar 

  34. Sun Z, Xie H, Zheng J, Man Z, He D (2021) Path-following control of Mecanum-wheels omnidirectional mobile robots using nonsingular terminal sliding mode. Mech Syst Signal Process 147:107128–107128

    Google Scholar 

  35. Hu C, Wang R, Yan F, Chen N (2016) Output constraint control on path following of four-wheel independently actuated autonomous ground vehicles. IEEE Trans Veh Technol 65(6):4033–4043

    Google Scholar 

  36. Liao J, Chen Z, Yao B (2019) Model-based coordinated control of four-wheel independently driven skid steer mobile robot with wheel-ground interaction and wheel dynamics. IEEE Trans Ind Inform 15(3):1742–1752

    Google Scholar 

  37. Guo J, Luo Y, Li K (2018) An adaptive hierarchical trajectory following control approach of autonomous four-wheel independent drive electric vehicles. IEEE Trans Intell Transp Syst 19(8):2482–2492

    Google Scholar 

  38. Begnini M, Bertol DW, Martins NA (2017) A robust adaptive fuzzy variable structure tracking control for the wheeled mobile robot: Simulation and experimental results. Control Eng Pract 64:27–43

    Google Scholar 

  39. Kong L, He W, Yang C, Li Z, Sun C (2019) Adaptive fuzzy control for coordinated multiple robots with constraint using impedance learning. IEEE Trans Cyber 49(8):3052–3063

    Google Scholar 

  40. Chwa D (2012) Fuzzy adaptive tracking control of wheeled mobile robots with state-dependent kinematic and dynamic disturbances. IEEE Trans Fuzzy Syst 20(3):587–593

    Google Scholar 

  41. Hou Z-G, Zou A-M, Cheng L, Tan M (2009) Adaptive control of an electrically driven nonholonomic mobile robot via backstepping and fuzzy approach. IEEE Trans Control Syst Technol 17(4):803–815

    Google Scholar 

  42. Park BS, Yoo SJ, Park JB, Choi YH (2009) Adaptive neural sliding mode control of nonholonomic wheeled mobile robots with model uncertainty. IEEE Trans Control Syst Technol 17(1):207–214

    Google Scholar 

  43. Taghavifar H, Rakheja S (2020) A novel terramechanics-based path-tracking control of terrain-based wheeled robot vehicle with matched-mismatched uncertainties. IEEE Trans Veh Technol 69(1):67–77

    Google Scholar 

  44. Bhat SP, Bernstein DS (2000) Finite-time stability of continuous autonomous systems. SIAMJ Control Optim 38(3):751–766

    MathSciNet  MATH  Google Scholar 

  45. Franceschelli M, Pisano A, Giua A, Usai E (2015) Finite-time consensus with disturbance rejection by discontinuous local interactions in directed graphs. IEEE Trans Autom Control 60(4):1133–1138

    MathSciNet  MATH  Google Scholar 

  46. Du H, Cheng Y, He Y (2014) Finite-time synchronization of a class of second-order nonlinear multi-agent systems using output feedback control. IEEE Trans Circuits Syst I Reg Papers Pap 61(6):1778–1788

    Google Scholar 

  47. Chen Q, Ren X, Na J, Zheng D (2017) Adaptive robust finite-time neural control of uncertain PMSM servo system with nonlinear dead zone. Neural Comput Appl 28:3725–3736

    Google Scholar 

  48. Cai M, Xiang Z (2018) Adaptive finite-time control of a class of non-triangular nonlinear systems with input saturation. Neural Comput Appl 29:565–576

    Google Scholar 

  49. Peng X, Wu H (2020) Non-fragile robust finite-time stabilization and \(H_{\infty }\) performance analysis for fractional-order delayed neural networks with discontinuous activations under the asynchronous switching. Neural Comput Appl 32:4045–4071

    Google Scholar 

  50. Slotine JJE, Li WP (1991) Applied nonlinear control. Prentice-Hall, New Jersey

    MATH  Google Scholar 

  51. Hardy G, Littlewood J, Polya G (1952) Inequalities. Cambridge University Press, Cambridge

    MATH  Google Scholar 

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Acknowledgements

This work was supported in part by the Natural Science Foundation of Shandong Province for Excellent Young Scholars in Provincial Universities under Grant ZR2018JL022, in part by the Science and Technology Plan for Young Talents in Colleges and Universities of Shandong Province under Grant 2020KJN007, in part by the Natural Science Foundation of Shandong Province under Grant ZR2018MF003, and in part by the National Natural Science Foundation of China under Grant 61773149, Grant 61772309, and Grant 92067108.

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Authors and Affiliations

  1. School of Computer Science and Technology, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353, Shandong, People’s Republic of China

    Xiaozheng Jin, Zhiye Zhao & Xiaoming Wu

  2. Shandong Computer Science Center (National Supercomputer Center in Jinan), Jinan, 250014, Shandong, People’s Republic of China

    Xiaozheng Jin, Zhiye Zhao & Xiaoming Wu

  3. Shandong Laboratory of Computer Networks, Jinan, 250014, Shandong, People’s Republic of China

    Xiaozheng Jin, Zhiye Zhao & Xiaoming Wu

  4. Department of Computer Science and Technology, Shandong University of Finance and Economics, Jinan, 250014, Shandong, People’s Republic of China

    Jing Chi

  5. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Chao Deng

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  1. Xiaozheng Jin
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Correspondence to Xiaozheng Jin or Jing Chi.

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Jin, X., Zhao, Z., Wu, X. et al. Adaptive NN-based finite-time trajectory tracking control of wheeled robotic systems . Neural Comput & Applic 34, 5119–5133 (2022). https://doi.org/10.1007/s00521-021-06021-7

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